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Original Articles and Reviews
Religiosity’s Nomological
Network and Temporal Change
Introducing an Extensive Country-Level Religiosity Index
based on Gallup World Poll Data
Mohsen Joshanloo
1
and Jochen E. Gebauer
2,3
1
Department of Psychology, Keimyung University, Dalseo-Gu, Daegu South Korea
2
Department of Psychology, University of Mannheim, Germany
3
Department of Psychology, University of Copenhagen, Denmark
Abstract: Countries differ in their religiosity and these differences have been found to moderate numerous psychological effects. The
burgeoning research in this area creates a demand for a country-level religiosity index that is comparable across a large number of countries.
Here, we offer such an index, which covers 166 countries and rests on representative data from 1,619,300 participants of the Gallup World Poll.
Moreover, we validate the novel index, use it to examine temporal change in worldwide religiosity over the last decade, and present a
comprehensive analysis of country-level religiosity’s nomological network. The main results are as follows. First, the index was found to be a
valid index of global religiosity. Second, country-level religiosity modestly increased between 2006 and 2011 and modestly decreased between
2011 and 2017 –demonstrating a curvilinear pattern. Finally, nomological network analysis revealed three things: it buttressed past evidence
that religious countries are economically less developed; it clarified inconsistencies in the literature on the health status of inhabitants from
religious countries, suggesting that their psychological and physical health tends to be particularly good once economic development is
accounted for; and finally, it shed initial light on the associations between country-level religiosity and various psychological dimensions of
culture (i.e., Hofstede’s cultural dimensions and country-level Big Five traits). These associations revealed that religious countries are primarily
characterized by high levels of communion (i.e., collectivism and agreeableness). We are optimistic that the newly presented country-level
religiosity index can satisfy the fast-growing demand for an accurate and comprehensive global religiosity index.
Keywords: religiosity, culture, country-level religiosity index, gallup
Culture has profound effects on human thought, feeling,
and behavior. The focal cultural dimension in the social
sciences across recent decades was the individualism-
collectivism dimension (Oyserman, Coon, & Kemmelmeier,
2002;Triandis,1995). More recently, however, psycholo-
gists have focused their attention on other cultural dimen-
sions, with one of them being country-level religiosity
(Diener, Tay, & Myers, 2011; Sedikides & Gebauer,
2010). A focus on country-level religiosity is warranted on
at least two counts. Firstly, few other cultural dimensions
encompass a similarly broad range. For example, there
are many countries where almost all inhabitants are reli-
gious (e.g., most African countries), but there are also coun-
tries where the majority of inhabitants are not religious
(e.g., most Scandinavian countries; Gebauer et al., 2014;
Joshanloo, 2019). Secondly, religiosity comes with a partic-
ularly large set of values, norms, and habits, which pro-
foundly influence virtually all aspects of culture (Cohen &
Hill, 2007; Gebauer, Sedikides, & Schrade, 2017). To illus-
trate, higher income predicts higher well-being (Diener, Ng,
Harter, & Arora, 2010), but this classic effect is diminished
in religious countries, where religious anti-wealth norms
prevail (e.g., “It is easier for a camel to go through the
eye of a needle than for someone who is rich to enter the
kingdom of God”,Mark10:25) (Gebauer, Nehrlich,
Sedikides, & Neberich, 2013). Along similar lines, positive
affective experiences predict higher life satisfaction (Cohn,
Fredrickson, Brown, Mikels, & Conway, 2009), but that
effect is diminished in religious countries (Joshanloo,
2019), where religious anti-pleasure norms are in place
(e.g., “Frustration is better than laughter, because a sad face
is good for the heart. The heart of the wise is in the house of
mourning, but the heart of fools is in the house of
pleasure”, Ecclesiastes 7:3–4).
In order to understand the influence of the religious
cultural climate on the human psyche, it is essential to pos-
sess knowledge about a country’s degree of religiosity, or –
in more technical terms –to possess a valid and globally
comparable religiosity index. The need for such an index
is particularly pressing at present, because religiosity has
become a mainstream topic in psychology (Saroglou,
2014; Sedikides, 2010). Resting on representative data from
Ó2019 Hogrefe Publishing European Psychologist (2019)
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1,619,300 individuals and spanning 166 countries, the pre-
sent research provides the most updated and inclusive
index of country-level religiosity. Moreover, we use this
index to gauge the change of global religiosity over the past
decade and to provide a thorough analysis of country-level
religiosity’s nomological network.
Existent Country-Level Religiosity Indices
A few country-level religiosity indices already exist in the
social science literature. All these indices have one thing
in common. Specifically, they estimate the religiosity of a
country by averaging the religiosity of individual partici-
pants in that country. Put differently, they aggregate indi-
vidual-level responses to the country-level –aprocedure
that has been commonplace in sociology for decades
(Books & Prysby, 1988;Stipak&Hensler1982). The differ-
ence between existent country-level religiosity indices,
then, is the nature of the individual-level data.
Perhaps the most widely used index in the social sciences
has been compiled by sociologist Phil Zuckerman (2007).
Zuckerman’s index describes the percentage of atheists
per country. The index makes use of individual-level data
from multiple sources. Notably, though, the different
sources report very different results for the same country.
Consequently, for most counties, Zuckerman reports per-
cent-ranges, rather than single percentages, and those
ranges frequently possess wide margins (e.g., Denmark:
43%–80%, Finland: 28%–60%, Russia: 24%–48%).
More recent country-level religiosity indices rely on data
from a single source. Some of those indices do not rely on
representative samples per country (Gebauer et al., 2014;
Gebauer, Paulhus, & Neberich, 2013). Other indices do rely
on representative samples, but sample size per country is
relatively small and/or the small number of countries in
the index leaves room for improvement and/or the distri-
bution of countries is biased toward western, industrialized
countries (e.g., Fincher & Thornhill, 2012). Moreover, exis-
tent indices rely on data that have been assessed over the
course of several years. It is possible, however, that coun-
try-level religiosity changes so rapidly that it is not reason-
able to aggregate the data across several years. Finally,
existent country-level religiosity indices have been related
to only few other country-level variables. Hence, we know
little about the nomological network of national religiosity.
Temporal Change in Country-Level
Religiosity
It is no exaggeration to state that psychologists have ignored
temporal change in country-level religiosity. Psychology’s
stance is hard to understand given that country-level
religiosity is a consequential moderator of individual-level
effects (Gebauer, Nehrlich, et al., 2013; Joshanloo, 2019).
For example, individual-level religiosity is associated with
psychological health benefits, but those benefits appear to
be restricted to religious countries (Gebauer, Sedikides, &
Neberich, 2012; Gebauer, Sedikides, Schönbrodt, et al.,
2017). Findings such as these suggest that psychologists
need to study the temporal change in country-level religios-
ity in order to estimate how individual-level effects of
religiosity will change in more secularized/religious futures.
If, for example, country-level religiosity further declines in
Western European countries (Edgell, 2012; Stark &
Iannaccone, 1994), the psychological health benefits of
religiosity may vanish altogether in those countries.
In contrast to the practices of psychologists, sociologists
have long sought to understand temporal change in
country-level religiosity. Dating back to Max Weber
(1930), secularization theory (Gorski & Altınordu, 2008;
Norris & Inglehart, 2011) has been the predominant theory
over much of sociology’s history. Stark and Iannaccone
(1994,p.230) pointedly described the theory and its
prevalence:
“For years everyone has agreed that many nations in
Europe are extremely secularized –that few attend
church services, that belief is on the wane, and that
the power and presence of religion in public life has
faded to a shadow of past glories... There also has
been nearly universal agreement that Europe’s secu-
larization represented the future of all societies –that
the spread of science and modernity doomed
religion.”
However, over the last 25 years or so, market theory
(Sherkat & Ellison, 1999;Warner,1993)hasbegunto
replace secularization theory as the predominant theory
of temporal change in country-level religiosity. Edgell
(2012,p.249) succinctly summarizes the theory:
“Market theory, in all its major variants, explicitly
challenges secularization theory’s core argument that
religion is a poor fit in the modern world. Market the-
orists argue that modernity creates the conditions
that foster religious privatization, pluralism, and vol-
untarism, causing religion to thrive –and, ironically,
to retain much of its public significance.”
How has country-level religiosity changed worldwide over
the last decade? The data used in the present study offer
a unique opportunity to test this question. Secularization
theory predicts a steady decline, whereas market theory
predicts little change. Both theories are broad, macro-level
theories. Yet, the last decade has seen a number of very
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specific historical events that may have influenced country-
level religiosity over and above the general influences pre-
dicted by secularization theory and market theory. The rise
of Islamist terrorism, for example, may have damaged the
reputation of religions in general. Alternatively, it may have
led religious people to stand by their religiosity even more
firmly in order to profess solidarity with peaceful and
wrongly accused religions. The latter effect may be most
visible among Muslims, because Muslims may feel a partic-
ularly strong need to display solidarity due to external pres-
sures and tensions. Regardless of reasons, it is timely and
important to examine temporal change in worldwide reli-
giosity over the last decade. That temporal change is not
only an interesting topic of inquiry in itself; it is also rele-
vant for our country-level religiosity index. If the change
was too vast, it would be inappropriate to base our coun-
try-level religiosity index on data from a whole decade.
Nomological Network of Country-Level
Religiosity
Cronbach and Meehl (1955) considered it essential to
understand the nomological network of any construct. For
individual-level constructs, psychologists have unanimously
endorsed that view. For country-level constructs, however,
nomological network analyses are rare (if existing at all).
This is not to say that country-level religiosity has never
been related to other country-level constructs. However,
those analyses have been rather limited and unsystematic.
A brief review that describes what we know so far about
country-level correlates of country-level religiosity follows.
To begin with, there is firm evidence that religiosity is
higher in economically less developed countries (Barro &
McCleary, 2003; Oishi & Diener, 2014). Compared to sec-
ular countries, religious countries possess a lower gross
domestic product (GDP) per capita (Rees, 2009), more
income inequality (Gini coefficient; Barber, 2011), a larger
proportion of agricultural employment (Barber, 2013), less
tertiary education (i.e., viewer postsecondary programs;
Barber, 2013), and lower scores on the Human Develop-
ment Index (HDI; Gaskins, Golder, & Siegel, 2013). These
associations are consistent with secularization theory,
according to which, the upsurge of scientific knowledge
(e.g., higher education) causes declines in religiosity,
because religious explanations of how the “world works”
are increasingly perceived as unlikely. The associations,
however, are also consistent with need-based theories of
religion (Sedikides, 2010). According to those theories,
religiosity becomes less important in economically devel-
oped countries, because economic development satisfies
many psychological needs for which human beings had to
rely on religiosity before (e.g., control –Kay, Gaucher,
McGregor, & Nash, 2010; psychological security –Diener
et al., 2011).
There is also evidence that people in religious countries
are psychologically and physically less healthy than people
in secular countries. Compared to inhabitants of secular
countries, those of religious countries were found to evalu-
ate their life more negatively and report more negative feel-
ings (Diener et al., 2011). Notably, though, controlling for
country-level economic development diminished (or even
reversed) those associations (Deaton & Stone, 2013). Inhab-
itants of religious countries were also found to commit sui-
cide more frequently, but controlling for country-level
economic development reversed that effect (Stack, 1983).
Regarding physical health, religious countries were found
to possess higher rates of infant and maternal mortality
and the life expectancy in religious countries were found
to be lower than in secular countries (Reeve, 2009). Again,
controlling for country-level economic development dimin-
ished those associations (and in one case, they disappeared
altogether).
Of note, there are exceptions to the just-described pat-
tern of results. For example, Diener et al. (2011)foundno
association between country-level religiosity and country-
level positive feelings, and Gebauer, Sedikides, Schönbrodt,
et al. (2017) found a positive association between religiosity
and self-esteem at the country-level. Similarly, two investi-
gations found a negative association between country-level
religiosity and country-level suicide rates even when no
covariates were included (Neeleman, Halpern, Leon, &
Lewis, 1997; Oishi & Diener, 2014). Together, the literature
on country-level religiosity and psychological and physical
health is less consistent than the literature on country-level
religiosity and economic development. Thus, the former lit-
erature is in particular need of additional evidence. For that
reason, we included many health variables in our nomolog-
ical network analysis.
Finally, little is known about the associations between
country-level religiosity and traditional cultural variables,
such as Hofstede’sfourdimensionsofculture–that is, indi-
vidualism, masculinity, power distance, and uncertainty
avoidance (Hofstede, Hofstede, & Minkov, 2010). Excep-
tions include two recent studies that found religious coun-
tries to be less individualistic than secular ones (Gebauer,
Sedikides, Schönbrodt, et al., 2017;Oishi&Diener,2014).
To our knowledge, it has not yet been tested whether that
association persists when country-level economic develop-
ment is controlled for. Hofstede’sfourdimensionscapture
many psychological differences between countries, but
these dimensions certainly do not capture all those differ-
ences. Rentfrow, Gosling, and their colleagues have shown
that geographical units also differ from each other along
the Big Five personality dimensions –that is, agreeableness,
conscientiousness, extraversion, openness to experience,
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and neuroticism (Rentfrow, 2010; Rentfrow, Gosling, & Pot-
ter, 2008). Yet, the associations between country-level reli-
giosity and country-level Big Five personality have not yet
been studied, even though there is much research on those
associations at the individual level (Gebauer et al., 2014;Sar-
oglou, 2010). The present research sought to close these
gaps in the literature.
Methods
Participants
The present research capitalizes on 2005–2017 data from
the Gallup World Poll (GWP). The GWP currently continu-
ally surveys residents in 167 countries and uses randomly
selected, nationally representative samples. Typically,
Gallup annually surveys 1,000 individuals over 15 years
of age in each country. Unfortunately, in some countries
data have not been collected in some years, and/or data
collection has started later than 2005. The present research
relies on all available GWP data, consisting of 1,862,900
participants across 166 countries (age: M=40.97,SD =
17.47;sex:53.4%women).
1
Electronic Supplementary
Material (ESM 1) includes the countries’names, gender
ratios, average ages, and national sample sizes.
Measures
Religiosity Index
The GWP measures religiosity with the following item: “Is
religion an important part of your daily life?”Responses are
coded as “yes,”“no,”“don’tknow,”and “refused.”From
the data, 1,619,300 participants answered this question.
The country-level religiosity index was calculated as the
percentage of people per country who responded with
“yes”(i.e., stated that religiosity is an important part in their
daily lives).
2
The External Measure of Religiosity
The World Values Survey (Inglehart et al., 2014) includes
multiple religiosity items. We z-standardized and averaged
four of them to yield an individual-level measure that fits
common definitions of general religiosity (Gebauer & Maio,
2012; Hill & Hood, 1999): (1) religious self-categorization
(“Independently of whether you go to church or not, would
yousayyouareareligiousperson”), (2) belief in God
(“Which, if any, of the following do you believe in?:
God”), (3) church attendance (“Apart from weddings,
funerals and baptisms, about how often do you attend reli-
gious services these days?”), and (4)habitsofprayer(“Do
you take some moments of prayer, meditation or contem-
plation or something like that?”). In a second step, we aver-
aged participants’general religiosity within each country.
We expected a high correlation between this measure and
our new index of country-level religiosity.
Prosperity
The nine sub-indices of the Legatum Prosperity Index
(Legatum Institute, 2017) assess (1) economic quality,
(2) business environment, (3) governance, (4) personal free-
dom, (5) social capital, (6) safety and security, (7) education,
(8)health,and(9) natural environment. Each sub-index
consists of dozens of objective and subjective variables.
Space does not permit to provide more details, but detailed
information can be obtained from http://www.prosperity.
com. We used the economic quality sub-index as a general
measure of economic progress and national wealth in our
analyses.
3
Health Security and Ecological Stress
Barber (2013) used country-level pathogen prevalence as an
estimate of health security. We included country-level
pathogen prevalence for the same reason in our analyses,
utilizing Fincher and Thornhill’s(2012)indexofnon-
zoonotic parasite prevalence (i.e., the prevalence of dis-
ease-causing parasites, which are transmittable between
human beings). Along Barber’s(2013) line of reasoning, cli-
matic harshness (i.e., very hot summers and/or very cold
winters) can influence health security and is associated with
pathogen prevalence (Van de Vliert, 2013). Thus, we
included these variables in our analyses, utilizing Van de
Vliert’s(2013) indices of cold demand (an estimate of
hotness in the summer) and heat demand (an estimate of
coldness in the winter).
1
The GWP includes one additional country (Oman), but the religiosity measure has never been administered in this country. We, thus, excluded
that country.
2
Diener et al. (2011) used the same procedure to estimate country-level religiosity on the basis of an early version of the GWP dataset. Diener
et al.’s version includes data across 4 years only (2005–2009). It also includes only about a quarter of the participants of the current GWP.
Additionally, it includes about 10% fewer countries. Finally, it includes relatively more Western countries. Joshanloo (2019) used a similar
version of the country-level religiosity index described in the present article to test a hypothesis about life satisfaction.
3
It is noteworthy that some of the prosperity variables rely on the GWP items that we also use here. For example, some of the affect items that we
use in our analyses (i.e., enjoyment, smile, and sadness) have been used to construct the health sub-index. However, given that we use these
variables in separate analyses, the overlap does not affect our analyses.
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Depression and Anxiety
The 2015 data from the Global Burden of Disease Study
(Institute for Health Metrics and Evaluation, 2015) provides
indices of disability-adjusted life years due to depression
and anxiety, including years of life lost from premature
death and years lived with less than full health.
Suicide Rate
We used the World Health Organization age-standardized
suicide rates per country for the year 2015 (http://www.
who.int/gho/en/).
Hedonic Well-Being
Eight aspects of hedonic well-being are measured by items
from the GWP: (1) present life satisfaction, (2) future life
satisfaction, (3) enjoyment, (4) laughter, (5)worry,(6)sad-
ness, (7) stress, and (8)anger.ESM2includes those items.
We averaged each item within each country to construct
country-level scores.
Purpose in Life
Purpose in life is measured in the GWP with the following
item: “Do you feel your life has an important purpose or
meaning?”From 2008 to 2011, the item has been used in
a small number of countries only and it was completely
excluded from the GWP after 2011. Therefore, this variable
is available for a smaller number of countries.
Eudaimonic Well-Being
The national eudaimonic well-being index (Joshanloo,
2018) based on data from 2005–2017 was used to measure
optimal functioning. This index is composed of seven GWP
items measuring learning experience, social support,
respect, efficacy beliefs, sense of freedom, and prosociality.
Human Development Index
The 2015 HDI index was obtained from http://hdr.undp.
org/en/data.
Hofstede’s Dimensions of National Culture
We measured Hofstede’s four cultural dimensions (individ-
ualism, masculinity, power distance, and uncertainty avoid-
ance) with country-level scores from Hofstede et al. (2010).
Big Five Personality Traits
Countries differ in their inhabitants’average agreeableness,
conscientiousness, extraversion, openness for experience,
and neuroticism. We used country-level scores based on
the Big Five Inventory (John, Donahue, & Kentle, 1991),
obtained from Gebauer et al. (2015).
Self-Esteem
Countries differ in their inhabitants’average self-esteem.
Gebauer et al. (2015) reported a country-level self-esteem
score based on a version of the Single-Item Self-Esteem
Scale (Robins, Hendin, & Trzesniewski, 2001), which is
used here.
Results and Discussion
Descriptive Statistics
As a reminder, the GWP assesses religiosity with the follow-
ing question: “Is religion an important part of your daily
life?”71.4% of the participants responded with “yes,”
26.9% responded with “no,”and only 1.3% responded with
“don’tknow”(0.4% refused to answer the question).
Table 1includes the national averages (i.e., the country-
level religiosity index) and Figure 1is a graphical display
of those averages. Mean country-level religiosity was
73.6%(min=15.8%, max = 98.9%, SD =24.5%).
Relationship With the External Measure of
Religiosity
Our country-level religiosity index rests on a single item
only. At the individual level, single items are often
described as unreliable (albeit single-item measures of reli-
giosity do not appear to suffer from low reliability; Gebauer,
Paulhus, et al., 2013). Importantly, aggregation to the coun-
try-level should average out any possible unreliability of sin-
gle-item measures. To empirically corroborate this logic
and to test whether our country-level religiosity index cap-
tures global religiosity adequately, we examined the associ-
ation between our index and the external measure of global
religiosity from the World Values Survey. As expected, the
association was near-perfect, r(95)=.894,p<.001.To
examine the robustness of this association, we split the
GWP data of each country in two random halves and calcu-
lated two independent country-level religiosity indices, each
one based on one half of the GWP data. The association
between those two GWB-based religiosity indices and the
external measure of global religiosity were, r(95)=.893,
p<.001, and, r(95)=.895,p<.001 (the two GWB-based
indices were also near perfectly intercorrelated,
r(166)=.999,p<.001). This suggests that our country-
level religiosity index is a robust index of religiosity at the
country-level.
Temporal Change in Country-Level
Religiosity
We conducted a latent growth curve analysis to examine
the global, temporal change in country-level religiosity
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between 2006 and 2017.
4
Latent growth curve modeling
defines two higher-order latent variables, one capturing
initial status (intercept) and the other one capturing rate
of change (slope). The mean and variance estimates for
the rate of change factor were of particular interest. The
mean estimate indicates the magnitude and direction of
average national change over time, whereas the variance
estimate indicates whether there are significant differences
between countries regarding the rate of change (Duncan &
Duncan, 2004;Preacher,2008). Our latent growth curve
model used country-level religiosity per year as manifest
indicators. We used Mplus 8.0(Muthén & Muthén, 2017)
for data analysis and estimated our models with Robust
Maximum Likelihood (MLR) estimation and handled miss-
ing data via Full Information Maximum Likelihood (FIML).
ESM 3includes the annual religiosity scores for each
country.
A linear growth curve model (with slope factor loadings
of 0–11 for the 12 years) yielded the following fit indices:
w
2
(73)=232.957,p<.001;RMSEA=0.115,CFI=0.947.
A quadratic growth curve model (with centered time codes:
5.5,4.4,3.5,2.5,1.5,0.5,0.5,1.5,2.5,3.5,4.5,
5.5) provided superior fit: w
2
(69)=177.793,p<.001;
RMSEA = 0.097,CFI=0.964. We chose to base our
Table 1.National religiosity scores
Country Score Country Score Country Score Country Score Country Score
1. Somaliland 98.9 35. Morocco 94.7 69. Bolivia 88.2 103. Turkmenistan 73.3 137. Canada 41.4
2. Sri Lanka 98.6 36. Nepal 94.5 70. Botswana 87.5 104. Cyprus 72.8 138. Lithuania 41.2
3. Indonesia 98.4 37. Mauritius 94.5 71. Benin 87.5 105. Moldova 72.7 139. Switzerland 40.8
4. Bangladesh 98.2 38. Jordan 94.4 72. El Salvador 87.3 106. Armenia 72.1 140. Hungary 39.7
5. Malawi 98.1 39. Burundi 94.4 73. Angola 87.0 107. Greece 71.3 141. Germany 39.5
6. Egypt 97.8 40. Swaziland 94.4 74. Guyana 86.8 108. Bosnia Herz 71.1 142. Bulgaria 39.4
7. Comoros 97.8 41. Kenya 94.1 75. Colombia 86.8 109. Kyrgyzstan 70.1 143. Spain 39.0
8. Ethiopia 97.5 42. Ghana 94.1 76. Cambodia 86.7 110. Nagorno Karabakh 70.0 144. Slovenia 37.5
9. Yemen 97.5 43. Cameroon 94.0 77. Togo 86.5 111. Chile 68.0 145. Latvia 36.4
10. Afghanistan 97.4 44. Pakistan 94.0 78. Ecuador 85.7 112. Poland 66.9 146. Luxembourg 35.3
11. Niger 97.4 45. Palestine 93.9 79. Trinidad and Tobago 85.2 113. Italy 65.2 147. Belarus 35.2
12. Senegal 97.2 46. UAE 93.7 80. Nicaragua 85.2 114. Belize 65.1 148. Iceland 34.6
13. Bhutan 97.2 47. Rwanda 93.7 81. Lebanon 85.2 115. USA 65.0 149. Vietnam 34.0
14. Mauritania 97.0 48. Congo Kinshasa 93.7 82. South Africa 85.1 116. Northern Cyprus 64.1 150. Cuba 33.5
15. Somalia 97.0 49. Liberia 93.5 83. Iraq 85.0 117. Croatia 63.7 151. Belgium 33.5
16. Sierra Leone 96.7 50. Algeria 92.9 84. Honduras 84.6 118. Argentina 63.4 152. Russia 32.9
17. Cent. Af. Republic 96.7 51. Chad 92.7 85. Malta 84.0 119. Mexico 63.3 153. Australia 32.3
18. Libya 96.6 52. Madagascar 92.5 86. Peru 83.3 120. Singapore 62.5 154. New Zealand 32.1
19. Djibouti 96.3 53. Tunisia 92.3 87. Puerto Rico 83.2 121. Portugal 61.9 155. Finland 31.0
20. Saudi Arabia 96.2 54. South Sudan 91.6 88. Panama 83.0 122. Montenegro 58.1 156. Netherlands 30.6
21. Guinea 96.1 55. Sudan 91.4 89. Jamaica 82.7 123. Uzbekistan 58.0 157. United Kingdom 29.9
22. Tanzania 96.0 56. Burkina Faso 91.2 90. Syria 82.6 124. Serbia 54.9 158. France 28.8
23. Thailand 95.7 57. Kuwait 91.2 91. India 82.5 125. Ireland 54.6 159. Czech Republic 25.5
24. Gambia 95.7 58. Namibia 90.8 92. Iran 82.5 126. Albania 52.0 160. Japan 24.8
25. Laos 95.7 59. Congo Brazzaville 90.5 93. Costa Rica 82.3 127. Slovakia 47.7 161. Hong Kong 24.8
26. Myanmar 95.3 60. Ivory Coast 90.4 94. Romania 81.6 128. Austria 46.4 162. Norway 21.9
27. Mali 95.3 61. Malaysia 90.0 95. Kosovo 81.4 129. Taiwan 46.0 163. Estonia 20.4
28. Bahrain 95.1 62. Mozambique 90.0 96. Haiti 80.6 130. South Korea 45.2 164. Denmark 19.4
29. Nigeria 95.1 63. Paraguay 89.8 97. Georgia 80.5 131. Israel 45.0 165. Sweden 18.8
30. Lesotho 95.0 64. Brazil 89.4 98. Turkey 79.7 132. Kazakhstan 44.8 166. China 15.8
31. Qatar 94.9 65. Gabon 89.2 99. Suriname 78.6 133. Mongolia 44.6
32. Uganda 94.9 66. Zimbabwe 88.8 100. Tajikistan 78.2 134. Ukraine 43.1
33. Zambia 94.8 67. Guatemala 88.4 101. Venezuela 78.1 135. Uruguay 42.6
34. Philippines 94.8 68. Dominican Rep. 88.4 102. Macedonia 76.0 136. Azerbaijan 42.0 Total 73.6
4
We excluded the year 2005 from these analyses, because religiosity data from that year were available for 26 countries only.
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analyses on the quadratic model, because the quadratic
model yielded better fit than the linear model, Δw
2
(4)=
56.183,p<.001. Consequently, we will not discuss the lin-
ear model any further.
The value of national religiosity at the mid-point of the
study (between the years 2011 and 2012) was estimated
to be 74.040%. There were significant differences in the
mid-point levels of religiosity between nations (variance =
597.004,p<.001). During the 12-year period, the linear
trajectory was not significant (M=0.028,p=0.683),
5
yet the quadratic trajectory was significant (M=0.038,
p=.003). These results suggest that the global level of reli-
giosity has followed a quadratic trajectory over the past
12 years and Figure 2displays that trajectory. The rates of
linear change (variance = 0.581,p<.001) and quadratic
change (variance = 0.015,p<.001) varied significantly
between nations.
In a follow-up analysis, we conducted a latent class
growth curve analysis to assess heterogeneity in the trajec-
tories of religiosity across identifiable groups of countries.
For this purpose, the quadratic growth curve model was
extended to incorporate categorical latent classes (Muthén
&Muthén,2000). We tested models with one, two, three,
and four classes. To choose the optimal number of
classes, we relied on the Bayesian Information Criterion
(BIC), the sample-size adjusted BIC (SSABIC), entropy,
the Lo-Mendell-Rubin adjusted likelihood ratio test (LMR-
LRT), and the bootstrapped LRT (BLRT). ESM 4includes
those results. Given that entropies and BLRTs were not
much different across the four models, we relied on BIC,
SSABIC, and LMR-LRT. The three- and four-class models
had better BIC/SSABIC values than the two-class model.
Hoverer, the LMR-LRT value for the four-class model did
not show a significant improvement over the three-class
model. Therefore, we selected the three-class model as
the optimal model. Figure 3and ESM 5show the country
classification.
The linear and quadratic slopes were not significant in
Groups 1and 2(brown and purple groups in Figure 3). In
Group 3(green), the linear component of the slope was
not significant (M=0.088,p=.167), but the quadratic com-
ponent was (M=0.053,p=.005). This pattern suggests a
quadratic trajectory in the 101 countries of Group 3,which
seems to account for the global quadratic trend given the
relatively large size of this group. Figure 4showsthisquad-
ratic trajectory. The average intercepts were 65.417%
(Group 1), 35.796%(Group2), and 91.037 (Group 3), indi-
cating that what distinguishes Group 3from the other two
groups is its higher average level of religiosity. In sum, these
results suggest that the quadratic global trend is largely
accounted for by a rather small quadratic trajectory in
highly religious nations.
Figure 1. Religiosity across 166 countries.
5
The mean of the linear trajectory represents the estimate of the instantaneous rate of change at the midpoint of the study.
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M. Joshanloo & J. E. Gebauer, Country-Level Religiosity 7
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Trends for Christianity and Islam From
2008 to 2017
In order to measure the rate of change for major religious
affiliations, we ran five separate analyses, one analysis for
each of the five major religious denominations. For Chris-
tianity, in a first step, we recoded religiosity-responses from
non-Christian participants to “0.”In essence, the newly cal-
culated item is conceptually equivalent to the following
statement: “Is Christianity an important part of your daily
life?”Next, we averaged the responses to that Christianity
item across all participants in each country. This procedure
was repeated for Islam, Buddhism, Hinduism, and secular-
ism/no religion. In many countries, there were very low
rates of respondents for Buddhism, Hinduism, and secular-
ism/no religion. As a result, the analyses involving those
religions did not converge. Thus, we only report the results
for Christianity and Islam. We examined linear models
only, because quadratic models did not converge either.
We excluded the years 2005–2007 from those analyses,
because of insufficient religion-specific data for those
years.
Figure 2. Sample and estimated means for national religiosity in the whole sample (2006–2017).
Figure 3. Country classification based on latent class growth analyses.
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Our religion-specific latent growth curve models used
religion-specific, country-level religiosity in each of the
10 years as manifest indicators. A linear growth curve
model of Christianity (with slope factor loadings of 0–9)
yielded the following fit indices: w
2
(50)=197.192,p<
.001;RMSEA=0.135,CFI=0.950. Based on the modifica-
tion indices, three covariances were specified to improve
model fit: between 2011 and 2012,2012 and 2013,
and 2011 and 2013. The modified model provided an
acceptable fit: w
2
(47)=115.567,p<.001;RMSEA=
0.095, CFI = 0.977. The initial level of global Christianity
was estimated to be 41.753%. There were significant differ-
ences in the average initial levels of Christianity between
nations (variance = 1,135.562,p<.001). During the 10-year
period, the rate of change for Christianity was negative,
very small, and significant (M=0.130,p=.036;see
Figure 5). The rates of change significantly varied across
nations (variance = 0.431,p<.001). These results suggest
a very small downward trend of global Christianity over
the last decade.
Among Muslims, a linear growth curve model yielded
acceptable fit indices: w
2
(50)=106.336,p<.001;RMSEA
=0.083,CFI=0.967. The initial level of Islamic religion
was estimated to be 25.484%. There were significant differ-
ences in the average initial levels of Islamic religion
between nations (variance = 1,319.498,p<.001). During
the 10-year period, the rate of change for Islam was
very small and nonsignificant (estimated to be 0.003,
p=.969). The rates of change significantly varied across
nations (variance = 0.463,p=.002). These results suggest
that the level of Islamic religion has not changed over the
past decade.
In all, we found nuanced and interesting patterns of tem-
poral change in religiosity over the last decade. Those
changes were not very large in size. This pattern of results
suggests that it is appropriate to base our country-level reli-
giosity index on all GWP data (i.e., data from 2005–2017).
Another way to probe for that suitability is to calculate 12
country-level religiosity indices –one for each year –and
to examine their interrelation. The interrelations between
those 12 indices were virtually perfect, mean r=.97 (.94
r.99). Hence, it appears justifiable to base our coun-
try-level religiosity index on all available GWP data (i.e.,
on data between 2005 and 2017).
Nomological Network of Country-Level
Religiosity
Table 2includes the correlations between our country-level
religiosity index and 36 other country-level variables.
6
To begin with, we probed for the well-documented associ-
ation between higher country-level religiosity and lower
economic development. We replicated that association.
6
We ran the same analyses in the two split samples, and found highly similar results (see ESM 6 and 7). This shows that all results are robust and
replicable.
Figure 4. Estimated means for national religiosity in Group 3 (2006–2017). ESM 10 presents the sample means.
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Compared to secular countries, religious countries evi-
denced (1) lower scores on the HDI, (2) lower economic
quality, (3) a worse business environment, (4) worse politi-
cal governance, (5) less safety and security, (6) less free-
dom, (7) less social capital, (8) worse performance in the
quality of the natural environment and preservation efforts,
and (9) worse education.
Next, we examined the association between country-
level religiosity and psychological and physical health. As
a reminder, the results on that issue have been somewhat
mixed in prior research (see Introduction). For the most
part, the prior results indicated that higher country-level
religiosity was associated with worse psychological and
physical health. Our non-adjusted correlation results were
in line with those prior results. Specifically, religious coun-
tries evidenced (1) lower life satisfaction, (2) less enjoyment,
(3) more worry, (4) more sadness, (5) higher anger, (6)a
worse health status,
7
and (7) lower health security (higher
pathogen prevalence) and more heat demand (but less cold
demand). On the other hand, country-level religiosity was
also unrelated to some health aspects and even positively
related to a few others. Specifically, country-level religiosity
was not associated with (1) future life satisfaction, (2)laugh-
ter, (3) stress, (4) eudaimonic well-being, and (5)suicide
rates. Moreover, people in religious countries evidenced
lower rates of disability due to (1) depression and (2)anxi-
ety, (3) reported higher self-esteem, and (4)muchmore
purpose in life. Thus, in line with past research, the health
status of religious countries was generally lower than that of
secular countries. Also in line with previous research, how-
ever, those results were less consistent than the results on
economic development.
Previous research has consistently shown that most neg-
ative associations between higher country-level religiosity
and worse health outcomes are largely due to the worse
economic development in religious countries (see Introduc-
tion). Put differently, there is little evidence that country-
level religiosity per se (i.e., once economic development is
controlled) is detrimental for psychological and physical
health. Thus, statistically controlling for economic develop-
ment should curb the negative associations between higher
country-level religiosity and worse health outcomes. This,
too, was the case with our data. Controlling for economic
quality
8
rendered nonsignificant four of the seven associa-
tions between country-level religiosity and health that were
previously significant (i.e., life satisfaction, worry, sadness,
and health). In addition, one previously negative association
turned positive (i.e., enjoyment). Only three associations
remained positive and significant indicating worse health
for religious nations (i.e., anger, pathogen prevalence, and
heat demand), but the size of those associations was
reduced. Plus, whereas the unadjusted association between
religiosity and stress was nonsignificant, it became positive
and significant once economic quality was controlled
Figure 5. Global change in Christianity between 2008 and 2017.
7
The prosperity health sub-index measures basic physical and mental health, health infrastructure, and preventative care.
8
Conceptually very similar results emerged when controlling for the HDI instead of economic quality. ESM 8 displays those results.
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for. Finally, controlling for economic quality turned signifi-
cant four of the five associations that were previously non-
significant(i.e.,morefuturelifesatisfaction,laughter,and
eudaimonic well-being, and lower suicide rates).
9
In all,
country-level religiosity per se does not appear to be associ-
ated with poorer country-level psychological and physical
health. To the contrary, results after controlling for eco-
nomic quality suggest that country-level religiosity is associ-
ated with certain health benefits.
A possible explanation for the latter may be the follow-
ing: Inhabitants of religious countries experience a greater
sense of purpose in life (Oishi & Diener, 2014)andthat
greater sense of purpose may explain the better rate of psy-
chological and physical health in religious countries.
Indeed, Oishi and Diener (2014) found initial evidence con-
sistent with this prediction. Specifically, they found that
country-level religiosity was associated with lower suicide
rates and that association was partly explained (i.e., medi-
ated) by a greater sense of purpose in religious countries.
A set of mediation analyses (see ESM 9) were partially con-
sistent with the just-described explanatory role of purpose
in life (for analog individual-level results; see Diener
et al., 2011).
Finally, we inspected the associations between country-
level religiosity and psychological dimensions of culture
(i.e., Hofstede’s cultural dimensions and country-level Big
Five traits). Country-level religiosity evidenced particularly
strong associations with two psychological dimensions of
culture (and those associations remained largely unaffected
by controlling for economic quality): higher collectivism
(i.e., lower individualism) and higher agreeableness
(Table 2). Collectivism and agreeableness can all be under-
stood as indicators of the even more fundamental dimen-
sion of communion (Abele & Wojciszke, 2014; Gebauer,
Leary, & Neberich, 2012). Thus, our findings resonate with
extensive research which shows that communion probably
is the most central abstract value across all world religions
(Gebauer, Paulhus, et al., 2013; Gebauer, Sedikides, &
Schrade, 2017).
Concluding Remarks
Countries differ widely in their degree of religiosity, and
those country-level differences qualify numerous psycholog-
ical effects that have been deemed universal (e.g., psycho-
logical health benefits of religiosity –Gebauer, Sedikides,
et al.,2012; psychological health benefits of income –
Gebauer, Nehrlich, et al., 2013; life satisfaction benefits
derived from affective experience –Joshanloo, 2019).
Table 2.Correlations with country-level religiosity
Variable rNr
p
N
p
Economic Development
HDI .715*** 158 .414*** 147
Economy .661*** 148 ––
Business .642*** 148 .193* 148
Governance .629*** 148 .237** 148
Safety/security .630*** 148 .272** 148
Freedom .564*** 148 .260** 148
Social capital .339*** 148 .198* 148
Environment .507*** 148 .142 148
Education .754*** 148 .489*** 148
Psychological and Physical Health
Life satisfaction .579*** 166 .140 148
Enjoyment .184* 166 .201* 148
Worry .158* 166 .014 148
Sadness .258** 166 .125 148
Anger .383*** 166 .242** 148
Health .614*** 148 .155 148
Pathogen prevalence .626*** 160 .380*** 148
Heat demand .517*** 160 .397*** 148
Cold demand .706*** 160 .616*** 148
Future life satisfaction .096 166 .157 148
Laughter .065 166 .381*** 148
Stress .066 166 .227** 148
Eudaimonic well-being .002 166 .326*** 148
Suicide .132 158 .218** 148
Depression .395*** 161 .217** 148
Anxiety .292*** 161 .082 148
Self-esteem .495*** 98 .325** 94
Purpose in life .664*** 132 .529*** 123
Psychological Dimensions of Culture
Power distance .465*** 69 .188 68
Individualism .570*** 69 .336** 68
Masculinity .124 69 .076 68
Uncertainty avoidance .186 69 .105 68
Extraversion .028 98 .076 94
Agreeableness .296** 98 .408*** 94
Conscientiousness .262** 98 .179 94
Openness .057 98 .097 94
Neuroticism .374*** 98 .208* 94
Note. r
p
= partial correlation controlling for economic quality. *p< .05; **p<
.01; ***p< .001.
9
Notably though, controlling for economic quality decreased all four previously positive associations between country-level religiosity and health.
Specifically, in two cases the associations were rendered nonsignificant (i.e., depression, and self-esteem) and in one case the association
changed signs (i.e., anxiety). Yet, the positive association between country-level religiosity and meaning in life remained strong and positive even
after economic quality was controlled for.
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M. Joshanloo & J. E. Gebauer, Country-Level Religiosity 11
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Hence, there is a great demand for a valid index of country-
level religiosity that is available for a large number of
countries. The present study provided such an index.
The index is based on representative data from 1,619,300
individuals and spans 166 countries worldwide. We made
use of that index to examine temporal change in worldwide
religiosity over the last decade and to gain a more complete
understanding of country-level religiosity’s nomological
network.
We found strong evidence that our country-level religios-
ity index is a valid and robust index of global religiosity.
More precisely, its correlation with an external four-item
index of global religiosity was near-perfect.
10
Moreover,
we randomly divided the full GWP sample into two inde-
pendent subsamples and used those subsamples to
compute two additional country-level religiosity indices.
Those two entirely independent country-level religiosity
indicators, too, correlated near-perfectly with the external
country-level index of global religiosity. That finding speaks
for the robustness of our index. The two independent
country-level religiosity indices also demonstrated a near-
perfect correlation, a finding that attests to the validity
and reliability of our index.
In addition, we estimated the worldwide temporal
change in religiosity between 2006 and 2017. We found a
quadratic trajectory (Figure 2). For the year 2006,weesti-
mated that 73.039% of the world population considered
religiosity an important part of their daily lives. From
2006 to 2011, we found an increase in worldwide religiosity
levels. By 2011, we estimated the highest level of religiosity
worldwide –74.044% of the world population considered
religiosity an important part of their daily lives. Finally,
from 2011 to 2017, we found a decrease in worldwide reli-
giosity. By 2017, the worldwide level of religiosity was
(descriptively) lower than in 2006 –72.725%oftheworld
population considered religiosity an important part of their
daily lives. Additional analyses identified a subset of 101
countries which drove the just-described quadratic trajec-
tory (Figure 3). Finally, we estimated the worldwide tempo-
ral changes in Christianity and Islam between 2008 and
2017. We found a small linear decline in Christianity from
41.753%in2008 to 40.582%in2017 and no significant
change in Islam within the same period of time (25.484%
in 2008 and 25.508%in2017). The small temporal change
over the last decade buttressed our decision to base our
country-level religiosity index on the cumulative data from
2005 to 2017. A detailed analysis of why we observed the
just-described pattern of temporal change is beyond the
scope of the present work, but it certainly is an interesting
and timely topic for future research. We acknowledge that
the temporal patterns we discovered in the present analyses
may be subject to unexpected changes in the near future,
and at present, it does not seem possible to predict the
future of worldwide religiosity.
Moreover, the present research includes the most com-
plete analysis of country-level religiosity’s nomological net-
work ever conducted, involving 36 external variables. First,
in replication of much previous research, country-level reli-
giosity was associated with lower economic development. It
is noteworthy that previous research typically capitalized on
a single indicator of economic development, whereas we
used several complementary indicators and found highly
convergent results. Second, we examined the association
between country-level religiosity and a large array of coun-
try-level health indicators (psychological health, physical
health, and health security). The results were less consistent
than in the case of economic development. However, on
the whole it seems fair to conclude that country-level reli-
giosity was mostly negatively related to health, but that neg-
ative relation was driven almost entirely by the poor
economic conditions in most religious countries. In fact,
after accounting for country-level differences in economic
conditions, religious countries were by and large healthier
than non-religious countries. Mediation analyses were lar-
gely consistent with Oishi and Diener’s(2014) proposal that
the health benefits of country-level religiosity are partly due
to higher levels of purpose in life in religious countries.
Finally, little has been known about the associations
between country-level religiosity and psychological dimen-
sions of culture (i.e., Hofstede’sculturaldimensionsand
country-level Big Five traits). We found that religious coun-
tries primarily differed from their non-religious counter-
parts on dimensions that belong to the fundamental
communion dimension (i.e., collectivism and agreeable-
ness; Abele & Wojciszke, 2014). This finding squares with
the high importance that all world religions place on com-
munal values and norms (Gebauer, Paulhus, et al., 2013;
Gebauer, Sedikides, & Schrade, 2017). Overall, the nomo-
logical network analysis conducted here buttressed
previous research, increased the confidence in our coun-
try-level religiosity index, and expanded our understanding
of country-level religiosity.
In conclusion, the present research introduced and vali-
dated the most extensive country-level religiosity index to
date, examined its worldwide temporal trajectory over the
last decade, and clarified its nomological network. We
(optimistically) hope that our country-level religiosity index
will be helpful for the large and fast-growing community of
scholars interested in the powerful role of country-level
religiosity for human thought, feelings, and behavior.
10
The existence of that external index does not render our index superfluous, because the external index only spans across 97 countries.
European Psychologist (2019) Ó2019 Hogrefe Publishing
12 M. Joshanloo & J. E. Gebauer, Country-Level Religiosity
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Electronic Supplementary Materials
The electronic supplementary materials are available with
the online version of the article at https://doi.org/
10.1027/1016-9040/a000382
ESM 1.Countries’names, number of participants, gender
ratios, and average ages.
ESM 2.Gallup world poll items used in the present
research.
ESM 3.National religiosity scores across years.
ESM 4.Results of latent class growth analyses.
ESM 5.Country classification based on latent class
growth curve analyses.
ESM 6. Correlations with religiosity at the national level
(half sample 1).
ESM 7. Correlations with religiosity at the national level
(half sample 2).
ESM 8. Correlations with religiosity at the national level
(whole sample) controlling for HDI.
ESM 9.Mediation analysis at the national level.
ESM 10.Sample means for national religiosity in the
third group.
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History
Received August 8, 2018
Revision received April 23, 2019
Accepted June 25, 2019
Published online December 6, 2019
European Psychologist (2019) Ó2019 Hogrefe Publishing
14 M. Joshanloo & J. E. Gebauer, Country-Level Religiosity
https://econtent.hogrefe.com/doi/pdf/10.1027/1016-9040/a000382 - Mohsen Joshanloo <mjoshanloo@hotmail.com> - Saturday, December 07, 2019 9:13:10 PM - IP Address:203.247.17.88
Acknowledgments
We would like to thank Professor Robert Dickey for his valuable
contributions.
Open Data
The Gallup World Poll data can be purchased at the following link:
https://www.gallup.com/home.aspx. Data from sources other
than Gallup are publicly available and can be obtained from
original sources. Detailed information about these data and their
sources are provided in the Methods section.
Funding
This work was supported by the Ministry of Education and
National Research Foundation of the Republic of Korea (NRF-
2017S1A3A2066611) and a grant from the German Research
Foundation (DFG; Grant GE 2515/6-1).
ORCID
Mohsen Joshanloo
https://orcid.org/0000-0001-9350-6219
Mohsen Joshanloo
Department of Psychology
Keimyung University
2800 Dalgubeol-Daero
Dalseo-Gu
Daegu 42601
South Korea
mjoshanloo@hotmail.com
Mohsen Joshanloo is an associate
professor of psychology at Keimyung
University, South Korea. His research
focuses on well-being, culture, reli-
gion, and measurement. Mohsen
Joshanloo completed his PhD in 2013
at Victoria University of Wellington,
New Zealand.
Jochen Gebauer is the Heisenberg-
Professor of Cross-Cultural Social
and Personality Psychology at the
University of Mannheim and Full
Professor of Social and Personality
Psychology at Copenhagen Univer-
sity. Jochen received his PhD from
Cardiff University, and held postdoc
positions at the University of
Southampton and the Humboldt-
University of Berlin.
Ó2019 Hogrefe Publishing European Psychologist (2019)
M. Joshanloo & J. E. Gebauer, Country-Level Religiosity 15
https://econtent.hogrefe.com/doi/pdf/10.1027/1016-9040/a000382 - Mohsen Joshanloo <mjoshanloo@hotmail.com> - Saturday, December 07, 2019 9:13:10 PM - IP Address:203.247.17.88
